I still can’t believe that we did that difficult epidural scenario right before it happened for real. We knew exactly what to do. So very proud of our teamwork. [Delivery suite team participant in simulation]
Practising speculum insertion on the pelvic model built my confidence before doing my first Pap smear. Although it was different on my patient, I’d rehearsed the manoeuvres and knew how to handle the speculum. [Medical student]
We tried out the functionality of our new delivery suite before it was fully fitted out by simulating a whole day of clinical practice. Probably saved a lot of money but even more importantly uncovered some flaws in our processes from patient and staff perspectives. [Hospital manager]
Introduction
Whether healthcare simulation is providing an opportunity to develop teamwork skills, build individuals’ confidence and psychomotor skills, or testing processes in a new facility, its impact can be profound. Simulation practice and research has matured sufficiently such that we need no longer focus on proving that it works, but on how to use it optimally and efficiently. The question is: how can we use simulation to support students and clinicians in developing safer practices and to design safer healthcare systems? The first chapter of an edited book is written with the intent of setting the scene. It is both a privilege and a responsibility to offer the foundations for the contributions from other authors. This book focuses on the use of simulation as an educational method and contributes to the broader conversation on safer healthcare systems. We start by defining simulation and describing the current healthcare landscape with reference to drivers for simulation uptake. We then offer an overview of simulation modalities and considerations for designing and implementing simulation-based education (SBE).
Scoping the Healthcare Simulation Landscape
Simulation is
a technique – not a technology – to replace or amplify real experiences with guided experiences that evoke or replicate substantial aspects of the real world in a fully interactive manner. (Gaba, 2007)
Healthcare simulation is not a new concept. Quite conversely, it has historical origins. Take, for example, Madam du Coudray’s fully simulation-based curriculum for midwives which was implemented in rural France in the eighteenth century (Owen, 2016). The drivers for that programme related in part to macro-level factors of the day. These agricultural populations were vulnerable to numerous socioeconomic stressors, among which high infant mortality made significant negative contribution. An important point here is that significant change occurred not because of evidence for the effectiveness of simulation but in response to large-scale social, economic and political demands. Today we are in a similar position, where our own modern macro-level factors are influencing simulation uptake. However, we are also equipped with knowledge about how simulation works, when and for whom. Empowered by this understanding, we can move towards addressing macro-level considerations, with simulation as an evidence-based and useful tool in our educational armamentarium.
What are some of these contemporary macro factors? Newspaper reports in 2017 document the apparently high numbers of infant deaths in one National Health Service (NHS) Trust in the United Kingdom (UK). Just as in eighteenth-century France, simulation could play a key role in addressing this issue. Despite recommendations from earlier investigations to improve professional practices and systems, the standards of care remain insufficient to meet societal expectations (Buchanan, 2017; Donnelly, 2017). The negative financial and reputational implications of these events to the NHS are significant. Perhaps even more so are the immeasurable emotional, psychological and social costs to the families and healthcare providers involved in adverse events. Although there can be no doubt that such expenses far outweigh the cost of targeted simulation training and systems testing, high-level political commitment is still required to effect change. In 2009, the UK’s Chief Medical Officer (Sir Liam Donaldson) wrote that simulation was one of the top priorities of the health services for the next decade (Donaldson, 2009). He emphasised the utility of simulation in rehearsal for emergency situations, for the fostering of teamwork and for the development of psychomotor skills in safe settings that do not place patients at risk. He also questioned the logic of charging clinicians to undertake training to make their practice safer.
In Australia, a macro driver for significant government investment in healthcare simulation infrastructure and faculty development was the estimated shortfall of clinical placement opportunities for healthcare students. Of course, patient safety is an important consideration, but the pressing need for training the future healthcare workforce remains. So far, investment has largely been at entry-level health professions (Australian Government Department of Health, 2015), although several initiatives were funded in 2010 for specialty medical and surgical training. However, only the Training in Professional Skills (TIPS) programme at the Royal Australasian College of Surgeons (RACS) has been sustained (Bearman et al., 2011, 2012).
Other drivers for SBE are well reported (Box 1.1). We have already identified patient safety and the expanding numbers of health professional students, while other key drivers may be values-based, education-focused, or initiatives at meso– or micro-level. The shift to competency-based education, combined with growing evidence supporting SBE as an effective instructional approach, is also important (Nestel et al., 2013). Herein, we are seeing accountability arising from published standards for simulation practice, certification of practitioners and accreditation of programmes. Higher-educational systems in healthcare now offer short and award courses which feature prominent roles for simulation, thus facilitating quality control and improvement, as well as mitigation of the human factors. There is a vibrant research community with new healthcare simulation-focused journals and several new textbooks such as this one. We provide a list of additional resources at the end of the chapter. It is also important to acknowledge that healthcare simulation is a billion-dollar global industry.
Box 1.1 Drivers for Uptake of Simulation-Based Education, Adapted from Nestel et al. (2011).
Values-based drivers
Ethical imperative of causing no harm to patients
Recognition of importance of patients’ perspectives
Responsibility of preparing healthcare practitioners to work in a changing clinical landscape
Education-oriented drivers
Facilitating a systematic approach to curriculum activities
Shifting to competency-based curricula
Assuring students/clinicians have direct/indirect exposure to certain clinical events
Allowing for adjustment in the level of challenge offered to participants
Identifying boundaries of competence of participants
Providing rehearsal and assessment of technical, communication and other professional skills essential for safe clinical practice
Enabling rehearsal of infrequently occurring events
Meso-level drivers
Growing prominence of the patient safety movement
Reducing length of hospital stays for patients and therefore reducing access to patients for learning
Growing evidence of simulation as an effective educational method
Increasing number of professional networks/societies/associations with a simulation orientation
Establishing standards for optimal simulation practice including certification of simulation practitioners, accreditation of simulation centres or programmes
Macro-level drivers
Working time directives/safer working hours initiatives
Maturing national quality improvement strategies
Growing prominence of the patient safety movement
Increasing numbers of medical and health professional students
Expanding national assessments for professional practice
Billion-dollar worldwide healthcare simulation industry
Healthcare simulation also has limitations and these are shared across the book. A major limitation remains the operational cost of simulation. An important area of research will be economic evaluations of SBE and other simulation applications (Maloney and Haines, 2016; Nestel et al., 2017). Further, assumptions are also often made about learning in simulation being safe. Although it is patient safe it is not necessarily safe for participants. High levels of stress, anxiety, different power relationships and the same sorts of physical risks of working in a clinical setting may all be present during SBE. Clinician safety is essential and it is incumbent on simulation practitioners to design safe learning environments in which all participants can develop their practice without harm.
Simulation Modalities
Simulation modalities are diverse. Most introductory books on healthcare simulation document these according to type and create a hierarchy of realism or fidelity – a highly contested notion (see later). We offer examples of core modalities and their combined use, especially in simulation scenarios. These modalities may be available in simulation centres and skills labs in higher education units and health services or may be offered onsite or in situ (Posner et al., 2017). See Chapter 5 for more information.
Simulated, or standardised, participants (SPs) refer to individuals who are paid or volunteers (patients, actors, health professionals or students) who are trained to portray specific roles within a simulation and to offer feedback to participants. As proxies for patients, SPs must be empowered to accurately represent (or simulate) them. Given that clinicians (with their own view of healthcare experiences) often train SPs, there can be challenges to the delivery of authentic patient perspectives (Nestel, 2015). (See example in Table 1.1.)
Table 1.1 Considerations of tasks for simulation practitioners using the simulation phases in three examples. For each example, we have assumed that the session is either mandated, addresses a curriculum gap, meets a clinical need or is experimental. It is not possible to include all tasks but we have attempted to identify some critical ones and those that characterise simulation as an educational method.
| SP-based formative assessment for medical students explaining vaginal examination and Pap smear to a patient | Laparoscopic simulator for trainees to learn basic skills | In situ delivery suite simulation with hybrid simulator for interprofessional collaborative practice | |
|---|---|---|---|
| Preparing |
|
|
|
| Briefing |
|
|
|
| Simulating |
|
|
|
| Debriefing/offering feedback |
|
|
|
| Reflecting |
|
|
|
| Evaluating |
|
|
|
1 Kurtz, S. and Silverman, J. (1996). The Calgary–Cambridge Referenced Observation Guides: an aid to defining the curriculum and organizing the teaching in communication training programmes. Medical Education, 30, 83–89.
2 Imperial College London. (2012). The London Handbook for Debriefing: Enhancing Performance Debriefing in Clinical and Simulated Settings. Retrieved from: https://workspace.imperial.ac.uk/ref/Public/UoA%2001%20-%20Clinical%20Medicine/lw2222ic_debrief_book_a5.pdf
3 Krogh, K., Bearman, M. and Nestel, D. (2015). Expert practice of video-assisted debriefing. Clinical Simulation in Nursing, 11, 180–187.
Task trainers enable participants to learn psychomotor skills applicable to procedures or operations. They vary in sophistication and technology from simple benchtop models (e.g. suturing, intubation) to sophisticated virtual reality models (e.g. laparoscopy; Aggarwal et al., 2007; Larsen et al., 2009) and virtual reality environments (Huber et al., 2018) (see example in Table 1.1).
Manikins are commonly used for developing team-based interprofessional care. They vary in technological sophistication and can be programmed to demonstrate physiological indicators of a patient’s condition. Depending on the manikin, participants can also undertake a diverse range of clinical procedures. Examples include SimMom (Laerdal; enabling SBE through all phases of labour) and Desperate Debra (Adam Rouilly; enabling SBE in the management of impacted fetal head at caesarean section).
Screen-based simulators use different technologies to provide learners with opportunities to develop knowledge of diverse clinical skills including diagnostic decision-making, steps in operative procedures, patient-centred communication and more. They often have a tremendous advantage of being highly accessible, including at the point of care.
Hybrid simulations are those in which simulation modalities are combined. They usually involve an SP with a task trainer (e.g. urinary catheter model, rectal examination model) and enable a staged approach to the development of psychomotor and communication skills (Higham et al., 2007).
Simulation-based training packages are widely available in obstetrics. Developed in the UK, PRactical Obstetric Multi-Professional Training (PROMPT) is designed to support the development of interprofessional collaborative practice for obstetric emergencies. The package is used internationally and has demonstrated direct improvements in perinatal outcome and improvements in practitioners’ knowledge, clinical skills and team-working (PROMPT – Making Childbirth Safer, Together, 2017). Advanced Life Support in Obstetrics (ALSO) and Become a Breech Expert (BABE) are Australian-based examples (Advanced Maternal and Reproductive Education).
Robotic surgery is emerging as a minimally invasive operative modality in gynaecology. Benefits over existing modalities include improved surgeon ergonomics, wristed nature of robotic instruments, and elimination of requirement for counterintuitive motion in the operative field. While we are watching this space, steady emergence of robotics must be recognised as limited by cost, access (currently available within the private health system only) and lack of robust data demonstrating global superior efficacy over techniques such as laparoscopy (Manolitsas, 2012). With increasing availability and utility of robotic surgery, simulation will play a key role in ensuring adequate operator training, maintenance of skills and patient safety.
Considerations in Designing Simulation-Based Education
McGaghie et al.’s (2010) review of the SBE literature identifies features and best practices for effective use of simulation as an educational method (see Box 1.2). Being well described both in their article and then throughout this book, it is beyond the scope of this chapter to discuss them in further detail. However, key points are that simulation is optimal when embedded in a curriculum or broader programme of learning activities relevant to the participants. Educational design is an overarching topic for many items in the list. The importance of setting and making explicit the educational objectives is emphasised. Opportunities for repetitive practice and feedback are highlighted. Selecting simulation modalities that are fit for purpose is important. Although included in the list, the notion of fidelity is contested, with some scholars recommending dropping the term. Hamstra et al. (2014) propose that functional task alignment and learner engagement are more useful concepts. Nestel et al. (2018) argue that the fidelity (or realism) of a simulator or a simulation depends in part on the participants’ willingness to engage in the activity ‘as if’ it were real (Dieckmann, 2009). They offer meaningfulness as a more useful concept for faculty involved in educational design. Finally, faculty development is considered critical; this includes acknowledgement that clinical experience is not a proxy for simulation instructor effectiveness.
Box 1.2 Features and Best Practices of Simulation-Based Education.
1. Feedback
2. Deliberate practice
3. Curriculum integration
4. Outcome measurement
5. Simulation fidelity
6. Skill acquisition and maintenance
7. Mastery learning
8. Transfer to practice
9. Team training
10. High-stakes testing
11. Instructor training
12. Educational and professional context
There are many theories that inform SBE from behaviourist, cognitivist and constructivist traditions. Each has a specific offering and may be valuable in considering SBE design, in understanding transfer of learning from simulation to real clinical settings, and in appreciating the variety of participants’ responses to engagement in simulation. Behaviourist theories are closely linked with the setting of learning objectives, of learning in response to a stimulus, of behaviour shaped by feedback. In SBE, the simulation activity becomes the stimulus and the briefing and debriefing (including feedback) helps to shape desired behaviour. The notions of deliberate practice as described by Ericsson (2015) and mastery learning applied extensively by McGaghie and his colleagues (McGaghie, 2015) are linked to this tradition, although they intersect with others too (Ericsson, 2015). Stimulus-response learning is insufficient in itself for sustained learning. Cognitivist theories of learning explore individuals’ thinking and knowing, memory capacities and problem-solving schema (Battista and Nestel, in press). Cognitive load theory is commonly cited by simulation educators in design considerations (Reedy, 2015). Too little or too much cognitive load at any stage of the simulation activity will influence capacity to learn. Finding the optimal load is the work of the simulation practitioner. While these two traditions have the learner at their centre, they focus on the teacher teaching. In the constructivist tradition, the experiences that learners bring to the learning are valued with the acknowledgement that individuals will make meaning for themselves. Reflective practice is commonly described as an illustration of a constructivist approach to learning (Schon, 1983). This theory proposes that during and after an unexpected or critical event, practitioners (learners) will reflect-in-action and reflect-on-action. Constructivist theories also acknowledge the context in which learning occurs and its social nature. Recently, attention has shifted to a range of complexity theories and the role of non-human objects and humans influencing learning, of the influence of the broader social and political environment (Battista, 2015, 2017; Fenwick and Dahlgren, 2015). The role of theory in SBE is further discussed in a series of articles (Eppich and Cheng, 2015; Husebo et al., 2015; Nestel and Bearman, 2015; Reedy, 2015).
Important considerations for any SBE activity are outlined in Box 1.3. Although there are limitations with oversimplifying complex processes, these defined phases help to remind the simulation practitioner of the interrelatedness of all activities. Box 1.3 illustrates these phases and Table 1.1 sets out the associated tasks for three different types of simulations.
Box 1.3 Phases in Simulation Design.
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